Abstract Directed Energy Deposition (DED) has become very popular for repair and rapid
prototy** in metal manufacturing industries. However, as an anisotropic and defect-prone …

Additive manufacturing (AM) is an emerging manufacturing technology that constructs
complex parts through layer-by-layer deposition. The prediction and control of thermal fields …

In this work, a data-driven framework based on Phase-Field simulations data is proposed to
highlight the capabilities of neural networks to ensure accurate low dimensionality reduction …

Directed energy deposition additive manufacturing (DED-AM) has gained significant interest
in producing large-scale metallic structural components. In this paper, a knowledge-based …

This article proposes an approach based on a feedforward neural network (FFNN-SM) and
computational simulations to rapidly predict thermal cycles in multi-layer single-bead walls …

Various data-driven modeling methods have been developed to predict the thermal field in
metal additive manufacturing (AM). The generalization capability of these models has been …

In this study, a data-driven deep learning model for fast and accurate prediction of
temperature evolution and melting pool size of metallic additive manufacturing processes …

The Directed Energy Deposition process is used in a wide range of applications including
the repair, coating or modification of existing structures and the additive manufacturing of …

Within the large Additive Manufacturing (AM) process family, Directed Energy Deposition
(DED) can be used to create low-cost prototypes and coatings, or to repair cracks. In the …

Thermal cladding is an effective method for protecting components from wear, corrosion,
and other forms of damage while providing additional insulation to reduce heat transfer. The …